A literature review on the use of retrospective LMS data to investigate online Teaching and Learning practices

K. Spreadborough, S. Glasser
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In these systems, pedagogical technologies are embedded in an infrastructure that enables administration and management of learning contents, communication, assessment, and collaboration (Washington, 2019). Due to the fact that the fundamental task of LMS is to support digital teaching and learning (El Bahsh & Daoud, 2016), they are some of the most extensively used learning technologies in higher education (Abazi-Bexheti, Jajaga, & Abazi-Alili, 2018). LMS technology is now widely adopted to support face-to-face, blended, and online pedagogical practices. In this context, LMS data provides large-scale capture, processing, and analysis of students’ interactions with the system, with each other, and with their teaching support within the system (Chung, 2014).  LMS data provides a rich resource through which to investigate online learning technologies and behaviours (see, for example, Chung, 2014). Such work is increasingly being done across multiple domains, however no systematic review has yet been conducted which surveys such work - specifically examining retrospective LMS data. This is the goal of the present paper. \n  \nA literature review was conducted to examine what data analysis methods have been used to better understand online pedagogy. The review focused specifically on the use of tertiary level retrospective LMS data and was not limited to a specific academic domain. The review was conducted from January - December 2021, with searching being conducted in January 2021. A total of 97 full text articles were included in the literature review. The literature review aimed to identify the kinds of research questions retrospective LMS data is being used to answer, the analytical techniques used to analyse this data, and the types of study designs used in this field of research. The number of students represented in the data and the academic domains were also considered. Quality of data and analytical reporting was assessed in order to interrogate the opportunities and challenges of reproducible research in studies using retrospective LMS data. Finally, the review considered the degree to which the analysis of retrospective LMS data met the needs of the research question. \n  \nUnderstanding how retrospective LMS data has been used to examine pedagogical practice in previous research equips us to reorientate Teaching and Learning in the immediate aftermath of COVID-19. This will become increasingly important as we move towards a future characterised by an escalation of remote and online learning opportunities. Through surveying previous research in this area, this paper provides an important foundation for future work utilising retrospective LMS data to understand online Teaching and Learning in the peri-COVID era. \n  \nReferences \n  \nAbazi-Bexheti, L., Kadriu, A., Apostolova-Trpkovska, M., Jajaga, E., & Abazi-Alili, H. (2018). LMS solution: Evidence of Google classroom usage inhigher education. Business Systems Research, 9(1), 31–43. https://doi.org/10.2478/bsrj-2018-0003 \nAl-Maroof, R. A. S., & Al-Emran, M. (2018). Students acceptance of Google classroom: An exploratory study using PLS-SEM approach. International Journal of Emerging Technologies in Learning (IJET), 13(06), 112. https://doi.org/10.3991/ijet.v13i06.8275 \nBahsh, R. El, & Daoud, M. I. (2016). Evaluating the use of Moodle to achieve effective and interactive learning : A case study at the German Jordanian University. In Proceedings of the 2nd international conference on open source software computing (OSSCOM 2016) (pp. 16–20). Beirut, Lebanon: IEEE \nBervell, B., & Umar, I. N. (2017). A decade of LMS acceptance and adoption research in sub-Sahara African higher education: A systematic review of models, methodologies, milestones and main challenges. Eurasia Journal of Mathematics, Science and Technology Education, 13(11), 7269–7286. https://doi. org/10.12973/ejmste/79444 \nBhat, S., Raju, R., Bikramjit, A., & Souza, R. D. (2018). Leveraging e-learning through Google classroom: A usability study. Journal of Engineering Education Transformations, 31(3), 1–7 \nButler-Henderson, K., Crawford, J., Rudolph, J., Lalani, K., & Sabu, K.M. (2020). COVID-19 in Higher Education Literature Database (CHELD V1): An open access systematic literature review database with coding rules. Journal of Applied Learning and Teaching, 3(3), DOI:https://doi.org/10.37074/jalt.2020.3.2.11 \nChung, G. K. W. K. (2014). Toward the Relational Management of Educational Measurement Data. Teachers College Record, 116(11), p. 1-16 \nCigdem, H., & Ozturk, M. (2016). Factors affecting students’ behavioral intention to use LMS at a Turkish post-secondary vocational school. International Review of Research in Open and Distributed Learning, 17(3). https://doi.org/10.19173/irrodl.v17i3.2253 \nKumar, J. A., Bervell, B., & Osman, S. (2020). Google classroom: insights from Malaysian higher education students’ and instructors’ experiences. Education and Information Technologies, 25(5), pp. 4175-4195. DOI: 10.1007/s10639-020-10163-x \nWashington, G. Y. (2019). The learning management system matters in face-to-face higher education courses. 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引用次数: 0

Abstract

Access to high quality education is a cornerstone of social, cultural, and economic recovery after any crisis. This is also true of the global COVID-19 pandemic which has disrupted the pedagogical practices of higher education institutions around the world (Butler-Henderson, Crawford, Rudolph, Lalani, & Sabu, 2020). Digital learning has become the new-norm, and tertiary education institutions have been propelled to innovate their teaching methods by integrating digital learning through the adoption of cost-effective (Al-Maroof & Al-Emran, 2018) and adaptable (Bhat et al., 2018) Learning Management Systems (LMS) (Bervell & Umar, 2017; Cigdem & Ozturk, 2016). In these systems, pedagogical technologies are embedded in an infrastructure that enables administration and management of learning contents, communication, assessment, and collaboration (Washington, 2019). Due to the fact that the fundamental task of LMS is to support digital teaching and learning (El Bahsh & Daoud, 2016), they are some of the most extensively used learning technologies in higher education (Abazi-Bexheti, Jajaga, & Abazi-Alili, 2018). LMS technology is now widely adopted to support face-to-face, blended, and online pedagogical practices. In this context, LMS data provides large-scale capture, processing, and analysis of students’ interactions with the system, with each other, and with their teaching support within the system (Chung, 2014).  LMS data provides a rich resource through which to investigate online learning technologies and behaviours (see, for example, Chung, 2014). Such work is increasingly being done across multiple domains, however no systematic review has yet been conducted which surveys such work - specifically examining retrospective LMS data. This is the goal of the present paper.   A literature review was conducted to examine what data analysis methods have been used to better understand online pedagogy. The review focused specifically on the use of tertiary level retrospective LMS data and was not limited to a specific academic domain. The review was conducted from January - December 2021, with searching being conducted in January 2021. A total of 97 full text articles were included in the literature review. The literature review aimed to identify the kinds of research questions retrospective LMS data is being used to answer, the analytical techniques used to analyse this data, and the types of study designs used in this field of research. The number of students represented in the data and the academic domains were also considered. Quality of data and analytical reporting was assessed in order to interrogate the opportunities and challenges of reproducible research in studies using retrospective LMS data. Finally, the review considered the degree to which the analysis of retrospective LMS data met the needs of the research question.   Understanding how retrospective LMS data has been used to examine pedagogical practice in previous research equips us to reorientate Teaching and Learning in the immediate aftermath of COVID-19. This will become increasingly important as we move towards a future characterised by an escalation of remote and online learning opportunities. Through surveying previous research in this area, this paper provides an important foundation for future work utilising retrospective LMS data to understand online Teaching and Learning in the peri-COVID era.   References   Abazi-Bexheti, L., Kadriu, A., Apostolova-Trpkovska, M., Jajaga, E., & Abazi-Alili, H. (2018). LMS solution: Evidence of Google classroom usage inhigher education. Business Systems Research, 9(1), 31–43. https://doi.org/10.2478/bsrj-2018-0003 Al-Maroof, R. A. S., & Al-Emran, M. (2018). Students acceptance of Google classroom: An exploratory study using PLS-SEM approach. International Journal of Emerging Technologies in Learning (IJET), 13(06), 112. https://doi.org/10.3991/ijet.v13i06.8275 Bahsh, R. El, & Daoud, M. I. (2016). Evaluating the use of Moodle to achieve effective and interactive learning : A case study at the German Jordanian University. In Proceedings of the 2nd international conference on open source software computing (OSSCOM 2016) (pp. 16–20). Beirut, Lebanon: IEEE Bervell, B., & Umar, I. N. (2017). A decade of LMS acceptance and adoption research in sub-Sahara African higher education: A systematic review of models, methodologies, milestones and main challenges. Eurasia Journal of Mathematics, Science and Technology Education, 13(11), 7269–7286. https://doi. org/10.12973/ejmste/79444 Bhat, S., Raju, R., Bikramjit, A., & Souza, R. D. (2018). Leveraging e-learning through Google classroom: A usability study. Journal of Engineering Education Transformations, 31(3), 1–7 Butler-Henderson, K., Crawford, J., Rudolph, J., Lalani, K., & Sabu, K.M. (2020). COVID-19 in Higher Education Literature Database (CHELD V1): An open access systematic literature review database with coding rules. Journal of Applied Learning and Teaching, 3(3), DOI:https://doi.org/10.37074/jalt.2020.3.2.11 Chung, G. K. W. K. (2014). Toward the Relational Management of Educational Measurement Data. Teachers College Record, 116(11), p. 1-16 Cigdem, H., & Ozturk, M. (2016). Factors affecting students’ behavioral intention to use LMS at a Turkish post-secondary vocational school. International Review of Research in Open and Distributed Learning, 17(3). https://doi.org/10.19173/irrodl.v17i3.2253 Kumar, J. A., Bervell, B., & Osman, S. (2020). Google classroom: insights from Malaysian higher education students’ and instructors’ experiences. Education and Information Technologies, 25(5), pp. 4175-4195. DOI: 10.1007/s10639-020-10163-x Washington, G. Y. (2019). The learning management system matters in face-to-face higher education courses. Journal of Educational Technology Systems, 1–21. https://doi.org/10.1177/0047239519874037
关于使用回顾性LMS数据调查在线教学实践的文献综述
获得高质量教育是任何危机后社会、文化和经济复苏的基石。全球COVID-19大流行也是如此,它扰乱了世界各地高等教育机构的教学实践(Butler-Henderson, Crawford, Rudolph, Lalani, & Sabu, 2020)。数字化学习已成为新常态,高等教育机构已被推动创新教学方法,通过采用具有成本效益的(al - maroof & al - emran, 2018)和适应性强的(Bhat等人,2018)学习管理系统(LMS) (Bervell & Umar, 2017;Cigdem & Ozturk, 2016)。在这些系统中,教学技术被嵌入到基础设施中,从而能够管理和管理学习内容、交流、评估和协作(Washington, 2019)。由于LMS的基本任务是支持数字化教学(El bahsh&daoud, 2016),它们是高等教育中使用最广泛的学习技术之一(Abazi-Bexheti, Jajaga, & Abazi-Alili, 2018)。LMS技术现在被广泛用于支持面对面、混合和在线教学实践。在这种情况下,LMS数据提供了大规模的捕获、处理和分析学生与系统、彼此之间以及与系统内教学支持的互动(Chung, 2014)。LMS数据为研究在线学习技术和行为提供了丰富的资源(参见,例如,Chung, 2014)。这类工作越来越多地在多个领域进行,但是尚未进行系统的审查来调查这些工作-特别是检查回顾性LMS数据。这就是本文的目标。我们进行了一项文献综述,以检查使用了哪些数据分析方法来更好地理解在线教学。该综述特别关注三级回顾性LMS数据的使用,并不局限于特定的学术领域。审查于2021年1月至12月进行,检索于2021年1月进行。文献综述共纳入97篇全文文章。文献综述的目的是确定使用回顾性LMS数据来回答的研究问题类型,用于分析这些数据的分析技术,以及在该研究领域中使用的研究设计类型。数据中所代表的学生人数和学术领域也被考虑在内。评估数据和分析报告的质量,以便在使用回顾性LMS数据的研究中询问可重复研究的机会和挑战。最后,综述考虑了回顾性LMS数据分析在多大程度上满足了研究问题的需要。了解回顾性LMS数据如何用于检查以往研究中的教学实践,有助于我们在2019冠状病毒病后立即重新调整教学方向。随着我们走向以远程和在线学习机会不断增加为特征的未来,这将变得越来越重要。本文通过对该领域已有研究的回顾,为今后利用回顾性LMS数据了解新冠肺炎时期在线教学提供了重要基础。参考文献Abazi-Bexheti, L., Kadriu, A., Apostolova-Trpkovska, M., Jajaga, E.和Abazi-Alili, H.(2018)。LMS解决方案:高等教育中谷歌课堂使用的证据。系统研究,9(1),31-43。https://doi.org/10.2478/bsrj-2018-0003 Al-Maroof, R. A. S., & Al-Emran, M.(2018)。学生对谷歌课堂的接受度:一项使用PLS-SEM方法的探索性研究。新技术在学习中的应用[j] .中文信息学报,2013(06),112。https://doi.org/10.3991/ijet.v13i06.8275 Bahsh, R. El, & Daoud, m.i.(2016)。评估Moodle的使用以实现有效和互动的学习:德国约旦大学的案例研究。第二届开源软件计算国际会议论文集(OSSCOM 2016) (pp. 16-20)。贝鲁特,黎巴嫩:IEEE Bervell, B., & Umar, i.n.(2017)。撒哈拉以南非洲高等教育中LMS接受和采用的十年研究:对模型、方法、里程碑和主要挑战的系统回顾。数学与科技教育,13(11),7269-7286。https://doi。Bhat, S., Raju, R., Bikramjit, A., and Souza, R. D.(2018)。利用谷歌课堂的电子学习:一项可用性研究。工程教育转型学报,31(3),1-7 Butler-Henderson, K., Crawford, J., Rudolph, J., Lalani, K.和Sabu, K.M.(2020)。新冠肺炎高等教育文献数据库(CHELD V1):开放获取的系统性文献综述数据库,有编码规则。 应用学习与教学学报,3(3),DOI:https://doi.org/10.37074/jalt.2020.3.2.11 Chung, g.k.w.k.(2014)。论教育测量数据的关联管理。《师范学院学刊》,116(11),p. 1-16。土耳其专上职业学校学生使用LMS行为意向的影响因素开放与分布式学习的国际研究综述,17(3)。https://doi.org/10.19173/irrodl.v17i3.2253 Kumar, J. A., Bervell, B., and Osman, S.(2020)。谷歌课堂:来自马来西亚高等教育学生和教师经验的见解。教育与信息技术,25(5),pp. 4175-4195。DOI: 10.1007/s10639-020-10163-x Washington, g.y.(2019)。学习管理系统在面授高等教育课程中起着重要的作用。教育技术系统学报,1-21。https://doi.org/10.1177/0047239519874037
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